H.264/MPEG-4 AVC [Joint Video Team of ITU-T VCEG and ISO/IEC MPEG, “Advanced Video Coding (AVC)—4th Edition,” ITU-T Rec. H.264 and ISO/IEC 14496-10 (MPEG4-Part 10), January 2005], which is incorporated by reference herein, is a video codec specification that uses macroblock prediction followed by residual coding to reduce temporal and spatial redundancy in a video sequence for compression efficiency. Spatial scalability refers to a functionality in which parts of a bitstream may be removed while maintaining rate-distortion performance at any supported spatial resolution. Single-layer H.264/MPEG-4 AVC does not support spatial scalability. Spatial scalability is supported by the Scalable Video Coding (SVC) extension of H.264/MPEG-4 AVC.
The SVC extension of H.264/MPEG-4 AVC [Working Document 1.0 (WD-1.0) (MPEG Doc. N6901) for the Joint Scalable Video Model (JSVM)], which is incorporated by reference herein, is a layered video codec in which the redundancy between spatial layers is exploited by inter-layer prediction mechanisms. Three inter-layer prediction techniques are included into the design of the SVC extension of H.264/MPEG-4 AVC: inter-layer motion prediction, inter-layer residual prediction, and inter-layer intra texture prediction.
Block based motion compensated video coding is used in many video compression standards such as H.261, H.263, H264, MPEG-1, MPEG-2, and MPEG-4. The lossy compression process can create visual artifacts in the decoded images, referred to as image artifacts. Blocking artifacts occur along the block boundaries in an image and are caused by the coarse quantization of transform coefficients.
Image filtering techniques can be used to reduce artifacts in reconstructed images. Reconstructed images are the images produced after being inverse transformed and decoded. The rule of thumb in these techniques is that image edges should be preserved while the rest of the image is smoothed. Low pass filters are carefully chosen based on the characteristic of a particular pixel or set of pixels surrounding the image edges.
Non-correlated image pixels that extend across image block boundaries are specifically filtered to reduce blocking artifacts. However, this filtering can introduce blurring artifacts into the image. If there are little or no blocking artifacts between adjacent blocks, then low pass filtering needlessly incorporates blurring into the image while at the same time wasting processing resources.
Previously, only dyadic spatial scalability was addressed by SVC. Dyadic spatial scalability refers to configurations in which the ratio of picture dimensions between two successive spatial layers is a power of 2. New tools that manage configurations in which the ratio of picture dimensions between successive spatial layers is not a power of 2 and in which the pictures of the higher level can contain regions that are not present in corresponding pictures of the lower level, referred to as non-dyadic scaling with cropping window, have been proposed.
All of the inter-layer prediction methods comprise picture up-sampling. Picture up-sampling is the process of generating a higher resolution image from a lower resolution image. Some picture up-sampling processes comprise sample interpolation. The prior up-sampling process used in the SVC design was based on the quarter luma sample interpolation procedure specified in H.264 for inter prediction. When applied to spatially scalable coding, the prior method has the following two drawbacks: the interpolation resolution is limited to quarter samples, and thus, is not supportive of non-dyadic scaling; and half-sample interpolation is required in order to get a quarter-sample position making this method computationally cumbersome. A picture up-sampling process that overcomes these limitations is desired.